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A Gabor Quotient Image for Face Recognition under Varying Illumination

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Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5359))

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Abstract

In this paper, we introduce a novel concept of illumination normalization for robust face recognition under different illumination conditions. The concept is extended from the Self Quotient Image (SQI) by which the 2D Gabor filter is applied instead of weighted Gaussian filter in order to increase more efficiency of the face recognition. Our experimental result, which is conducted on Yale face database B, has shown that our proposed method reached a very high recognition rate even in the case of extreme varying illumination.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Mahanakorn University of Technology, 51 Cheum-Sampan Rd., Nong Chok, Bangkok, Thailand, 10530

    Sanun Srisuk & Amnart Petpon

Authors
  1. Sanun Srisuk
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  2. Amnart Petpon
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

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© 2008 Springer-Verlag Berlin Heidelberg

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Srisuk, S., Petpon, A. (2008). A Gabor Quotient Image for Face Recognition under Varying Illumination. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_50

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  • DOI: https://doi.org/10.1007/978-3-540-89646-3_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89645-6

  • Online ISBN: 978-3-540-89646-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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